Welcome to the InfoSci Platform
Remote Monitoring and Recognition of Physical Activities of Elderly People Using Smartphone Accelerometer Sensor Data Using Deep Learning Models

Remote Monitoring and Recognition of Physical Activities of Elderly People Using Smartphone Accelerometer Sensor Data Using Deep Learning Models

Govind P. Gupta, Shubham Gaur
Copyright: © 2020 |Pages: 11
ISBN13: 9781522598183|ISBN10: 1522598189|EISBN13: 9781522598190
DOI: 10.4018/978-1-5225-9818-3.ch007
Cite Chapter Cite Chapter

MLA

Gupta, Govind P., and Shubham Gaur. "Remote Monitoring and Recognition of Physical Activities of Elderly People Using Smartphone Accelerometer Sensor Data Using Deep Learning Models." Handbook of Research on Health Systems and Organizations for an Aging Society, edited by César Fonseca, et al., IGI Global, 2020, pp. 90-100. https://doi.org/10.4018/978-1-5225-9818-3.ch007

APA

Gupta, G. P. & Gaur, S. (2020). Remote Monitoring and Recognition of Physical Activities of Elderly People Using Smartphone Accelerometer Sensor Data Using Deep Learning Models. In C. Fonseca, M. Lopes, D. Mendes, F. Mendes, & J. García-Alonso (Eds.), Handbook of Research on Health Systems and Organizations for an Aging Society (pp. 90-100). IGI Global. https://doi.org/10.4018/978-1-5225-9818-3.ch007

Chicago

Gupta, Govind P., and Shubham Gaur. "Remote Monitoring and Recognition of Physical Activities of Elderly People Using Smartphone Accelerometer Sensor Data Using Deep Learning Models." In Handbook of Research on Health Systems and Organizations for an Aging Society, edited by César Fonseca, et al., 90-100. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-5225-9818-3.ch007

Export Reference

Mendeley
Favorite

Abstract

Remote monitoring and recognition of physical activities of elderly people within smart homes and detection of the deviations in their daily activities from previous behavior is one of the fundamental research challenges for the development of ambient assisted living system. This system is also very helpful in monitoring the health of a swiftly aging population in the developed countries. In this chapter, a framework is proposed for remote monitoring and recognition of physical activities of elderly people using smart phone accelerometer sensor data using deep learning models. The main objective of the proposed framework is to provide preventive measures for the emergency health issues such as cardiac arrest, sudden falls, dementia, or arthritis. For the performance evaluation of the proposed framework, two different benchmark accelerometer sensor datasets, UCI and WISDM, are used. Results analysis confirms the performance of the proposed scheme in terms of accuracy, F1-score, root-mean square error (RMSE).

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.